DocumentCode :
2132181
Title :
Acoustic surveillance based on Higher-order Local Auto-Correlation
Author :
Sasou, Akira
Author_Institution :
Nat. Inst. of Adv. Ind. Sci. & Technol. (AIST), Japan
fYear :
2011
fDate :
18-21 Sept. 2011
Firstpage :
1
Lastpage :
5
Abstract :
The importance of video-surveillance applications has been increasing with the increase of crime and terrorism. In addition to traditional video cameras, the use of acoustic sensors in surveillance and monitoring applications is also becoming increasingly important. In this paper, we apply a High-order Local Auto-Correlation (HLAC) system, which has succeeded in video surveillance application, to extract features from acoustic signals for acoustic-surveillance systems. Experiment results confirmed that the proposed acoustic-surveillance system outperforms a cepstrum-based one under all SNR conditions.
Keywords :
acoustic signal processing; acoustic transducers; cepstral analysis; correlation methods; terrorism; video cameras; video surveillance; HLAC system; SNR conditions; acoustic sensors; acoustic signals; acoustic surveillance; acoustic-surveillance systems; cepstrum-based one; crime; high-order local auto-correlation system; higher-order local auto-correlation; monitoring applications; terrorism; video cameras; video-surveillance applications; Cepstrum; Feature extraction; Signal to noise ratio; Surveillance; Time frequency analysis; Vectors; Cepstrum; HLAC; acoustic surveillance;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning for Signal Processing (MLSP), 2011 IEEE International Workshop on
Conference_Location :
Santander
ISSN :
1551-2541
Print_ISBN :
978-1-4577-1621-8
Electronic_ISBN :
1551-2541
Type :
conf
DOI :
10.1109/MLSP.2011.6064587
Filename :
6064587
Link To Document :
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